Biomimetic rehabilitation engineering: the importance of somatosensory feedback for brain-machine interfaces

J Neural Eng. 2016 Aug;13(4):041001. doi: 10.1088/1741-2560/13/4/041001. Epub 2016 May 25.


Objective: Brain-machine interfaces (BMIs) re-establish communication channels between the nervous system and an external device. The use of BMI technology has generated significant developments in rehabilitative medicine, promising new ways to restore lost sensory-motor functions. However and despite high-caliber basic research, only a few prototypes have successfully left the laboratory and are currently home-deployed.

Approach: The failure of this laboratory-to-user transfer likely relates to the absence of BMI solutions for providing naturalistic feedback about the consequences of the BMI's actions. To overcome this limitation, nowadays cutting-edge BMI advances are guided by the principle of biomimicry; i.e. the artificial reproduction of normal neural mechanisms.

Main results: Here, we focus on the importance of somatosensory feedback in BMIs devoted to reproducing movements with the goal of serving as a reference framework for future research on innovative rehabilitation procedures. First, we address the correspondence between users' needs and BMI solutions. Then, we describe the main features of invasive and non-invasive BMIs, including their degree of biomimicry and respective advantages and drawbacks. Furthermore, we explore the prevalent approaches for providing quasi-natural sensory feedback in BMI settings. Finally, we cover special situations that can promote biomimicry and we present the future directions in basic research and clinical applications.

Significance: The continued incorporation of biomimetic features into the design of BMIs will surely serve to further ameliorate the realism of BMIs, as well as tremendously improve their actuation, acceptance, and use.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomedical Engineering / trends
  • Biomimetics / trends*
  • Brain-Computer Interfaces / trends*
  • Feedback, Physiological*
  • Humans
  • Rehabilitation / instrumentation*